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Platform for parallel computation in the Amazon cloud, including machine learning ensembles written in R for computational biology and other areas of scientific research. Home to MR-Tandem, a hadoop-enabled fork of X!Tandem peptide search engine.
This is a RapidMiner extension replacing the current Weka-Plugin with the updated 3.7.3 Weka-Version. This is basically a branch of the 3.7.3 Version of WEKA wrapped into the old extension. New Features Include:
-All the Features of the 3.7.3 Weka Package
-Multi-Threaded ensemble learning
-An enhancement on the popular RandomForest Learner based on "Dynamic Integration with Random Forests" by Tsymbal et al. 2006 and "Improving Random Forests" by Robnik-Sikonja 2004.
-More enhancements...
This project is devoted to the creation of an open source Error-Correcting Output Codes (ECOC) library for the Machine Learning community. The ECOC framework is a powerful tool to deal with multi-class categorization problems.
DOGMA is a MATLAB toolbox for discriminative online learning. It implements all the state of the art algorithms in a unique and simple framework. Examples are Perceptron, Passive-Aggresive, ALMA, NORMA, SILK, Projectron, RBP, Banditron, etc.
This RapidMiner-plugin consists of operators for feature selection and classification - mainly on high-dimensional (microarray-) data - and some helper-classes/operators.
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RobGP is a genetic programming system written from the ground up in C++. It's primary goals are efficiency, ease of use, and extensibility. It's distinguishing feature is that it has a modified version of Koza's architecture altering operations.
The Mars Rover Simulator project is based on the evolutionary robotics paradigm where an artificial agent acquires its skills through the process of artificial evolution. This simulator can be useful to evolve neural network controllers for the rover
RoboBeans is an interface to the "Robocup 2D Soccer Simulation Server" that allows developers to write Robocup teams\agents concentrating on behaviour and AI without having to worry about syntax of communication or network issues.
Feating constructs a classification ensemble comprising a set of local models. It is effective at reducing the error of both stable and unstable learners, including SVM. For details see the paper at http://dx.doi.org/10.1007/s10994-010-5224-5.
Leark is a Data Mining library developed in C#.NET. It contains several methods for ranking web documents described with a set of normalized features, and a feature selection algorithm. The methods are based on perceptron and clustering.
The aim of ALIVE is to develop new approaches to the engineering of flexible, adaptable distributed service-oriented systems based on the adaptation of social coordination and organisation mechanisms.
The data complexity library, DCoL, is a machine learning software that implements all metrics to characterize the apparent complexity of classification problems. The code is implemented in C++ and can be run on multiple platforms.
Content Addressable Memory, Multi-Variate Statistics, Data Mining Includes analyzing datasets, extracting patterns, creating empirical expert system. Computes joint probabilities and implements a "belief" as the solution of an equilibrium equation
The Python Computer Vision Framework is an opened project deisgned for all those interested in computer vision. It aims at making computer vision more easy and structured and matlab-free.
It may also be used for other artistic and scientific areas.
KeplerWeka adds the functionality of the open-source machine learning and data mining workbench WEKA to the free and open-source, scientific workflow application, Kepler.
BorderFlow implements a general-purpose graph clustering algorithm. It maximizes the inner to outer flow ratio from the border of each cluster to the rest of the graph.
SAIM allows to interlink knowledge bases in the Semantic Web. It focuses on instance matching of very large knowledge bases available as SPARQL endpoints. SAIM uses machine learning techniques and is compatible with SILK.